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In Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology

[18F]FDOPA PET imaging has shown dopaminergic function indexed as Kicer differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [18F]FDOPA PET approaches had good test-rest reproducibility across striatal regions (Kicer ICC: 0.68-0.94, SUVRc ICC: 0.76-0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach: Kicer = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (Kicer: ~50%, SUVRc: 40-60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [18F]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of ~£3400 (equivalent to $4232 USD) per patient. These findings indicate [18F]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.

Veronese Mattia, Santangelo Barbara, Jauhar Sameer, D’Ambrosio Enrico, Demjaha Arsime, Salimbeni Hugh, Huajie Jin, McCrone Paul, Turkheimer Federico, Howes Oliver